1. Field of the Invention
The present invention relates to encoding and decoding of a speech signal, and, more particularly, to a wide-band speech signal compression apparatus to compress a speech signal in a scalable bandwidth structure, a wide-band speech signal decompression apparatus to decompress the compressed speech signal, and a method thereof.
2. Description of the Related Art
An existing communication method based on Public Switched Telephone Network (PSTN) samples a speech signal at 8 kHz and transmits a speech signal with a bandwidth of 4 kHz. Accordingly, such a PSTN-based communication method cannot transmit speech signals of a frequency beyond 4 kHz, which deteriorates the voice quality of the speech signal.
To solve such a problem, a packet-based wide-band speech signal compression apparatus that samples a received speech signal at 16 kHz, and provides a speech signal with a bandwidth of 8 kHz, has been developed. However, although the quality of the speech signal improves as the bandwidth of the speech signal increases, the amount of data transmission of the communication channel increases. Therefore, to efficiently operate the wide-band speech signal compression apparatus, an adequate communication channel for transmitting large amounts of data should be ensured.
However, the amount of data transmission on the packet-based communication channel may be changed according to various factors. Accordingly, the adequate communication channel required by the wide-band speech signal compression apparatus may not be ensured, which can deteriorate the voice quality of the speech signal. That is, if the amount of data transmission on the communication channel is not enough at a specific moment, the speech packet is lost during transmission, so that the speech signal cannot be transmitted.
Accordingly, a technique which compresses speech signals by a scalable bandwidth has been proposed. An example of such a technique is ITU standard G.722. The ITU standard G.722 proposes a method that divides a received speech signal into two bands, using a low-pass filter and a high-pass filter, and compresses the respective bands individually. In the ITU standard G.722, the signals are compressed according to an Adaptive Differential Pulse Sign Modulation (ADPCM) method. However, the compression method proposed in the ITU standard G.722 has a very high data transmission rate.
Also, the ITU standard G.722.1 discloses a technique that converts a wide-band signal into a frequency-domain signal, divides the frequency-domain signal into several sub-band signals, and compresses the respective sub-band signals. However, the ITU standard G.722.1 is not compatible with a standard narrow-band speech signal compression apparatus, and it also does not construct a speech packet in a scalable bandwidth structure.
A conventional wide-band speech signal compression technique, developed to be compatible with a standard narrow-band speech signal compression apparatus, passes a wide-band speech signal through a low-pass filter to obtain a narrow-band speech signal, encodes the narrow-band speech signal using a standard narrow-band speech signal compressor, and compresses a high-band speech signal using a separate method. Here, packets of the narrow-band speech signal and the high-band speech signal are transmitted in a scalable structure.
A conventional technique for processing a high-band speech signal divides a high-band speech signal into a plurality of sub-band signals using a filter-bank, and compresses the respective sub-band signals. Another conventional technique for compressing a high-band speech signal converts the high-band speech signal into a frequency-domain signal by discrete cosine transform (DCT) or discrete Fourier transform (DFT) and quantizes the generated frequency coefficients individually.
However, since such wide-band speech signal compression techniques having a scalable bandwidth structure do not use the characteristics of the narrow-band speech signal when compressing the high-band speech signal, they have a low compression efficiency.
Also, since these wide-band speech signal compression techniques quantize all frequency coefficients converted to a frequency domain without efficient use of the correlation of intra-band and inter-band, they have a low quantization efficiency and a low prediction performance in decompressing information not transmitted when the signal was compressed.